RamanBench unifies 74 datasets into the first large-scale reproducible benchmark for ML on Raman spectra, finding tabular foundation models outperform baselines but no method generalizes across datasets.
Statistical comparisons of classifiers over multiple data sets.Journal of Machine learning research, 7(Jan):1–30
3 Pith papers cite this work. Polarity classification is still indexing.
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XAI explanations should be narratives with continuous structure, cause-effect, fluency and diversity, and new metrics are needed to evaluate this better than standard NLP scores.
Localized polygon-based models trained on clustered bus stops achieve prediction accuracy comparable to a single global model when using ridership, spatial, weather, and temporal features.
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RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy
RamanBench unifies 74 datasets into the first large-scale reproducible benchmark for ML on Raman spectra, finding tabular foundation models outperform baselines but no method generalizes across datasets.
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On the Importance and Evaluation of Narrativity in Natural Language AI Explanations
XAI explanations should be narratives with continuous structure, cause-effect, fluency and diversity, and new metrics are needed to evaluate this better than standard NLP scores.
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Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction
Localized polygon-based models trained on clustered bus stops achieve prediction accuracy comparable to a single global model when using ridership, spatial, weather, and temporal features.